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http://www.utsouthwestern.edu/education/medical-school/departments/neurology/programs/traumatic-brain-injury/index.html

The 16 affiliated Model System centers throughout the United States are responsible for gathering and submitting the core data set to the national database as well as conducting research studies on traumatic brain injury (TBI) both in collaboration with the other centers and within our own site. Through our research we hope to learn more about TBI and about the issues and concerns of people with TBI. Our goals are to improve the outcome and quality of life for people who have had brain injuries and for those who are caring for the person with a TBI. The North Texas Traumatic Brain Injury Model System (NT-TBIMS) pools the efforts and talents of individuals from the Departments of Neurosurgery, Neurology, Physical Medicine and Rehabilitation, Psychiatry (Neuropsychiatry), and Neuroradiology of the two leading medical institutions in the North Texas region. To be a patient involved in the research being conducted by the North Texas Traumatic Brain Injury Model System you must have suffered a TBI, be at least 16 years of age, have received initial treatment for the TBI at either Parkland Health and Hospital System or Baylor University Medical Center and then have received rehabilitative care at either Parkland, University Hospital Zale-Lipshy, or Baylor Institute for Rehabilitation. The patient must also be able to understand and sign an informed consent to participate or, if unable, have a family member or a legal guardian who understands the form sign the informed consent for the patient.

Proper citation: North Texas Traumatic Brain Injury Model System (RRID:SCR_005879) Copy   


  • RRID:SCR_005847

http://www.brainsmatter.com/

Welcome to the Brains Matter podcast where brains really do matter. A discussion of science, trivia, history, and general knowledge. The show started in September 2006, and includes discussion on various topics, as well as interviews with experts in their field. You can subscribe to the show via iTunes, a standard RSS reader, or listen to the individual MP3 shows from the ''flash player'' on the website, or direct download.

Proper citation: Brains Matter (RRID:SCR_005847) Copy   


  • RRID:SCR_005841

    This resource has 1+ mentions.

http://brainnetworks.sourceforge.net

Brain Networks: Code to perform network analysis on brain imaging data.

Proper citation: Brain Networks (RRID:SCR_005841) Copy   


http://adrc.ucsd.edu/

The UCSD ADRC conducts a wide variety of research studies dedicated to understanding the causes, clinical features, and treatments for Alzheimer's disease and related memory disorders. The goal of the center is to discover ways to prevent and eradicate the disease. The Center aims to maintain research subjects, clinical resources, and clinical data to support ongoing and proposed research and to assist in the development of new clinical and interdisciplinary research. An Alzheimer's brain bank with well characterized cases, including Mild Cognitive Impairment and Lewy Body disease, is maintained at the Center.

Proper citation: Shiley-Marcos Alzheimer's Disease Research Center (RRID:SCR_001928) Copy   


  • RRID:SCR_002249

    This resource has 10+ mentions.

http://www.thevirtualbrain.org/

Simulation software for modeling the entire human brain by combining structural and functional data from empirical neuroimaging data. It can generate local field potentials, EEG, MEG and fMRI BOLD data based on neural mass models. The user can also modify the model parameters to match clinical conditions from focal lesions or degenerative disorders.

Proper citation: Virtual brain (RRID:SCR_002249) Copy   


  • RRID:SCR_002166

    This resource has 10+ mentions.

http://www.nitrc.org/projects/voxbo

Software package for brain image manipulation and analysis, focusing on fMRI and lesion analysis. VoxBo can be used independently or in conjunction with other packages. It provides GLM-based statistical tools, an architecture for interoperability with other tools (they encourage users to incorporate SPM and FSL into their processing pipelines), an automation system, a system for parallel distributed computing, numerous stand-alone tools, decent wiki-based documentation, and lots more.

Proper citation: VoxBo (RRID:SCR_002166) Copy   


  • RRID:SCR_002241

    This resource has 50+ mentions.

https://www.humanbrainproject.eu/

Global, collaborative effort for neuroscience, medicine and computing to understand brain, its diseases and its computational capabilities. Goal is to obtain access to research, data sources, platforms and infrastructures offered by other organisations, and enabling organizations outside HBP to use HBP platforms to pursue their own research. Coordinating these activities is the responsibility of the European Research Programme.

Proper citation: Human Brain Project EU (RRID:SCR_002241) Copy   


  • RRID:SCR_002227

    This resource has 1+ mentions.

https://www.nitrc.org/projects/uncbcp_4d_atlas/

Software package for constructing longitudinal atlases, which are the necessary steps for many brain-related applications.

Proper citation: 4D Atlases Construction (RRID:SCR_002227) Copy   


http://olympus.magnet.fsu.edu/galleries/ratbrain/index.html

An image gallery of the rat brain labeled via immunofluorescence in coronal, horizontal, and sagittal thick sections using laser scanning confocal microscopy.

Proper citation: Confocal Microscopy Image Gallery - Rat Brain Tissue Sections (RRID:SCR_002432) Copy   


http://www.nitrc.org/projects/msseg

Training material for the MS lesion segmentation challenge 2008 to compare different algorithms to segment the MS lesions from brain MRI scans. Data used for the workshop is composed of 54 brain MRI images and represents a range of patients and pathology which was acquired from Children's Hospital Boston and University of North Carolian. Data has initially been randomized into three groups: 20 training MRI images, 24 testing images for the qualifying and 8 for the onsite contest at the 2008 workshop. The downloadable online database consists now of the training images (including reference segmentations) and all the 32 combined testing images (without segmentations). The naming has not been changed in comparison to the workshop compeition in order to allow easy comparison between the workshop papers and the online database papers. One dataset has been removed (UNC_test1_Case02) due to considerable motion present only in its T2 image (without motion artifacts in T1 and FLAIR). Such a dataset unfairly penalizes methods that use T2 images versus methods that don't use the T2 image. Currently all cases have been segmented by expert raters at each institution. They have significant intersite variablility in segmentation. MS lesion MRI image data for this competition was acquired seperately by Children's Hospital Boston and University of North Carolina. UNC cases were acquired on Siemens 3T Allegra MRI scanner with slice thickness of 1mm and in-plane resolution of 0.5mm. To ease the segmentation process all data has been rigidly registered to a common reference frame and resliced to isotrophic voxel spacing using b-spline based interpolation. Pre-processed data is stored in NRRD format containing an ASCII readable header and a separate uncompressed raw image data file. This format is ITK compatible. If you want to join the competition, you can download data set from links here, and submit your segmentation results at http://www.ia.unc.edu/MSseg after registering your team. They require team name, password, and email address for future contact. Once experiment is completed, you can submit the segmentation data in a zip file format. Please refer submission page for uploading data format.

Proper citation: MS lesion segmentation challenge 2008 (RRID:SCR_002425) Copy   


http://millette.med.sc.edu/Lab%209%2610/histology_of_nervous_tissue.htm

A website for a neuroscience lab class from the University of South Carolina that contains images of different parts of the nervous system and allows students to identify each part and answer questions about it. You should be able to (a) recognize nervous tissue in routine histological sections; (b) distinguish peripheral nerves from dense CT and smooth muscle; (c) recognize the morphological differences between myelinated and unmyelinated nerves at both the light microscopic and electron microscopic levels; (d) recognize nerve cell bodies and their component parts; (e) identify and differentiate dendrites and axons; (f) understand and identify various types of neuroglia, including Schwann cells; (g) understand and identify the structural relationship of the Schwann cell cytoplasm and plasma membrane enveloping axons; (h) understand the general features of nerve synapses. You should be able to draw nerves, cell bodies, Nodes of Ranvier, synapses etc. as they would appear under both the electron and light microscopes.

Proper citation: Histology of Nervous Tissue Laboratory Course (RRID:SCR_002367) Copy   


  • RRID:SCR_002470

    This resource has 10+ mentions.

http://www.med.unc.edu/bric/ideagroup/free-softwares/libra-longitudinal-infant-brain-processing-package

A toolbox with graphical user interfaces for processing infant brain MR images. Longitudinal (or single-time-point) multimodality (including T1, T2, and FA) (or single-modality) data can be processed using the toolbox. Main functions of the software (step by step) include image preprocessing, brain extraction, tissue segmentation and brain labeling. Linux operating system (64 bit) is required. A workstation or server with memory >8G is recommended for processing many images simutaneously. The graphical user interfaces and overall framework of the software are implemented in MATLAB. The image processing functions are implemented with the combination of C/C++, MATLAB, Perl and Shell languages. Parallelization technologies are used in the software to speed up image processing.

Proper citation: iBEAT (RRID:SCR_002470) Copy   


http://learn.genetics.utah.edu/content/addiction/

A physiologic and molecular look at drug addiction involving many factors including: basic neurobiology, a scientific examination of drug action in the brain, the role of genetics in addiction, and ethical considerations. Designed to be used by students, teachers and members of the public, the materials meet selected US education standards for science and health. Drug addiction is a chronic disease characterized by changes in the brain which result in a compulsive desire to use a drug. A combination of many factors including genetics, environment and behavior influence a person's addiction risk, making it an incredibly complicated disease. The new science of addiction considers all of these factors - from biology to family - to unravel the complexities of the addicted brain. * Natural Reward Pathways Exist in the Brain: The reward pathway is responsible for driving our feelings of motivation, reward and behavior. * Drugs Alter the Brain's Reward Pathway: Drugs work over time to change the reward pathway and affect the entire brain, resulting in addiction. * Genetics Is An Important Factor In Addiction: Genetic susceptibility to addiction is the result of the interaction of many genes. * Timing and Circumstances Influence Addiction: If you use drugs when you are an adolescent, you are more likely to develop lifetime addiction. An individual's social environment also influences addiction risk. * Challenges and Issues in Addiction: Addiction impacts society with many ethical, legal and social issues.

Proper citation: New Science of Addiction: Genetics and the Brain (RRID:SCR_002770) Copy   


http://www.cnl.salk.edu/

The long range goal of this laboratory is to understand the computational resources of brains from the biophysical to the systems levels. The central issues being addressed are how dendrites integrate synaptic signals in neurons, how networks of neurons generate dynamical patterns of activity, how sensory information is represented in the cerebral cortex, how memory representations are formed and consolidated during sleep, and how visuo-motor transformations are adaptively organized. Additionally, new techniques have been developed for modeling cell signaling using Monte Carlo methods (MCell) and the blind separation of brain imaging data into functionally independent components (ICA).

Proper citation: Computational Neurobiology Laboratory at the Salk Institute (RRID:SCR_002809) Copy   


https://med.uth.edu/nrc/

The Neuroscience Research Center (NRC) is a university-wide center where diverse and multidisciplinary research is conducted to further the understanding of neural and behavioral disorders. Whether conducting cellular research in laboratories or clinical trials in patient care settings, the work of NRC researchers may someday contribute to preventing and treating such devastating disorders as: * Dementias resulting from Alzheimer''s disease and stroke * Mental retardation and other learning disabilities * Mental illnesses, including schizophrenia and manic-depressive illness * Alcoholism and other substance abuse problems * Inability to process knowledge due to factors such as aging and head trauma * Disabilities due to disorders of the developing nervous system More than 280 faculty hold NRC appointments, and are on the faculties of the Medical School, School of Public Health, School of Nursing, Dental Branch, and School of Biomedical Informatics. Departments with significant NRC research activities within the Medical School include Neurobiology and Anatomy; Neurology; Neurosurgery; Ophthalmology and Visual Science; Psychiatry and Behavioral Sciences and Radiology. NRC activities are guided by an executive committee appointed by the President of the Health Science Center. The Neuroscience Research Center (NRC) is affiliated with educational opportunities at the graduate and postdoctoral levels.

Proper citation: UTHealth at Houston Neuroscience Research Center (RRID:SCR_007486) Copy   


  • RRID:SCR_008003

http://brancusi1.usc.edu/thesaurus/list/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19,2022. The BAMS Thesaurus is a part of the larger BAMS The Foundational Model of Connectivity (FMC). The principle of constructing the resource are: 1. Systematic attempts to produce internally consistent classifications and taxonomies require theoretical frameworks for deciding between alternatives. 2. Alternate classification and taxonomy schemes are always possible and must be accommodated. 3. The FMC is based on evidence, not authority. All components are justified by reference to the best observational or experimental evidence from the literature, combined with reference to priority when possible, not by undocumented statements from textbooks, the Web, or elsewhere. 4. The FMC is based on evolving evidence and concepts, revisions are based on enforced rules, and versioning is systematic and historical. The first version of FMC and the foundation of this online version was published in Swanson & Bota (2010). Please cite this reference whenever any part of the FMC is used in any way. This online version of FMC has the following main parts: 1. Thesaurus, which includes an alphabetical list of all concepts and terms used in FMC to date. The preferred terms are in bold. Clicking on each term of the Thesaurus will retrieve its definition, reference, list of synonyms, and a comment form that can be used by registered users. 2. References, which includes an alphabetical list of the literature used to construct FMC. Listed references are associated with the definitions included in the Thesaurus, and PubMed links. 3. Search form that can be used to search for terms defined in FMC, included in their definitions, their abbreviations, and references (search by authors). We strongly recommend to read FMC rules and notations before starting to use the online version.

Proper citation: BAMS Thesaurus (RRID:SCR_008003) Copy   


  • RRID:SCR_007973

    This resource has 100+ mentions.

http://enhancer.lbl.gov/

Resource for experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Most of these noncoding elements were selected for testing based on their extreme conservation in other vertebrates or epigenomic evidence (ChIP-Seq) of putative enhancer marks. Central public database of experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to particular tissue, or download entire collections of enhancers with defined tissue specificity or conservation depth.

Proper citation: VISTA Enhancer Browser (RRID:SCR_007973) Copy   


  • RRID:SCR_008020

    This resource has 10+ mentions.

http://www.buzsakilab.com/

Lab interested in understanding how neuronal circuitries of the brain support its cognitive capacities. Its goal is to provide rational, mechanistic explanations of cognitive functions at a descriptive level. In the lab''s view, the most promising area of cognitive faculties for scientific inquiry is memory, since it is a well-circumscribed term, can be studied in animals and substantial knowledge has accumulated on the molecular mechanisms of synaptic plasticity. Available software: * NeuroScope: NeuroScope can display local field potentials (EEG), neuronal spikes, behavioral events, as well as the position of the animal in the environment. It also features limited editing capabilities. * Klusters: Klusters is a powerful and easy-to-use cluster cutting application designed to help neurophysiologists sort action potentials from multiple neurons on groups of electrodes (e.g., tetrodes or multisite silicon probes). * KlustaKwik: KlustaKwik is a program for automatic cluster analysis, specifically designed to run fast on large data sets. * MATLAB m-files: A selection of MATLAB files developed in the lab., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Buzsaki Lab (RRID:SCR_008020) Copy   


http://www.nibb.ac.jp/brish/indexE.html

Database of detailed protocols for single and double in situ hybridization (ISH) method, probes used by Yamamori lab and others useful for studies of brain, and many photos of mammalian (mostly mouse and monkey) brains stained with various gene probes. Also includes a brain atlas of gene expression. Currently, the atlas comprises a series of un-annotated images showing the localization of a particular probe or molecule, e.g., AChE.

Proper citation: BraInSitu: A homepage for molecular neuroanatomy (RRID:SCR_008081) Copy   


http://sig.biostr.washington.edu/projects/brain/

The UW Integrated Brain Project is one project within the national Human Brain Project, a national multi-agency effort to develop informatics tools for managing the exploding amount of information that is accumulating about the human brain. The objective of the UW Integrated Brain Project effort is to organize and integrate distributed functional information about the brain around the structural information framework that is the long term goal of our work. This application therefore extends the utility of the Digital Anatomist Project by using it to organize non-structural information. The initial driving neuroscience problem that is being addressed is the management, visualization and analysis of cortical language mapping data. In recent years, advances in imaging technology such as PET and functional MRI have allowed researchers to observe areas of the cortex that are activated when the subject performs language tasks. These advances have greatly accelerated the amount of data available about human language, but have also emphasized the need to organize and integrate the sometimes contradictory sources of data, in order to develop theories about language organization. The hypothesis is that neuroanatomy is the common substrate on which the diverse kinds of data can be integrated. A result of the work done by this project is a set of software tools for generating a 3-D reconstruction of the patient''s own brain from MRI, for mapping functional data to this reconstruction, for normalizing individual anatomy by warping to a canonical brain atlas and by annotating data with terms from an anatomy ontology, for managing individual lab data in local laboratory information systems, for integrating and querying data across separate data management systems, and for visualizing the integrated results. Sponsors: This Human Brain Project research is funded jointly by the National Institute on Deafness and Other Communication Disorders, the National Institute of Mental Health, and the National Institute on Aging.

Proper citation: University of Washington Integrated Brain Project (RRID:SCR_008075) Copy   



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